## [1] 0.2023995
##
## Call:
## lm(formula = merged_subset$K01574 ~ merged_subset$log.flux.acetone)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0140 -0.6787 -0.5394 0.3149 2.4021
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.7352 0.6088 4.493 0.000369 ***
## merged_subset$log.flux.acetone 0.2964 0.3585 0.827 0.420561
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.025 on 16 degrees of freedom
## Multiple R-squared: 0.04097, Adjusted R-squared: -0.01897
## F-statistic: 0.6834 on 1 and 16 DF, p-value: 0.4206
## [1] 0.5316064
##
## Call:
## lm(formula = merged_subset$log.flux.acetone ~ merged_subset$log.flux.acetate)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.17162 -0.34942 -0.04867 0.37279 1.15749
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.9580 0.2786 3.439 0.00337 **
## merged_subset$log.flux.acetate 0.4692 0.1869 2.511 0.02318 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6052 on 16 degrees of freedom
## Multiple R-squared: 0.2826, Adjusted R-squared: 0.2378
## F-statistic: 6.303 on 1 and 16 DF, p-value: 0.02318
## [1] -0.08572158
##
## Call:
## lm(formula = merged_subset$log.flux.acetone ~ merged_subset$log.flux.diacetyl)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.5158 -0.3670 -0.1526 0.4063 1.0834
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.7342 0.5367 3.231 0.00523 **
## merged_subset$log.flux.diacetyl -0.1164 0.3382 -0.344 0.73521
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7119 on 16 degrees of freedom
## Multiple R-squared: 0.007348, Adjusted R-squared: -0.05469
## F-statistic: 0.1184 on 1 and 16 DF, p-value: 0.7352